AI in drug discovery & development: News watch, October 2026
Recent developments in the biopharma AI world include a $1.5 billion partnership between AstraZeneca and insitro, plus news from Iambic, DaltonTx, NVIDIA, and Chai Discovery.
AZ taps insitro AI platform for cardiometabolic disease R&D
AstraZeneca has agreed to pay insitro $40 million upfront to use the latter's AI-powered drug discovery platform to find new drug targets for liver and heart conditions, with another $1.46 billion on offer in potential development and commercial milestones.
The alliance will focus in particular on metabolic dysfunction-associated steatohepatitis (MASH) and cardiomyopathies, both "complex heterogeneous diseases where there is significant unmet need," according to AZ. The partners will apply insitro's Virtual Human platform – which applies machine learning, human genetics, lab models, and functional genomics to generate predictive in vitro models that provide insights into disease progression – to find novel targets and identify lead drug candidates. AZ will be responsible for running any future clinical trials.
"One of the most critical decisions in R&D is selecting the right target," said Sharon Barr, AZ's head of biopharmaceuticals R&D. "Partnering with insitro, we will use advanced AI to identify the biological drivers of disease to support the rapid discovery of high-quality novel targets, advancing our ambition to deliver the next generation of medicines to patients faster."
AZ adds to a growing roster of big pharma partners for South San Francisco-based insitro, a list that also includes Bristol Myers Squibb, Eli Lilly, and Gilead Sciences.
Iambic banks $150m from Nasdaq IPO
Iambic Therapeutics made its debut on the Nasdaq this week after selling 9.4 million shares at $16 – the midpoint of the range it was hoping for – raising around $150 million and giving it a valuation of more than $800 million.
The San Diego start-up – which has developed an AI platform based on a closed-loop system that combines AI with automated chemistry and biology lab capabilities – plans to use the funding to advance its lead in-house drug candidate IAM1363, an oral, brain-penetrating HER2 inhibitor in phase 1 testing. The drug is being developed for HER2-positive breast cancer and other HER2-altered tumours like non-small cell lung cancer (NSCLC), and Iambic is pitching to start a registrational trial for IAM1363 next year.
Iambic has also earmarked some of the IPO proceeds for the two following candidates in preclinical development: KIF18A-targeted IAM217 for breast and ovarian cancers and anti-CDK2/4 candidate IAM-C1, which is being developed for HR+/HER2- breast cancer and CCNE1-amplified tumours.
Shares in the company have started trading on the Nasdaq under the IAM ticker and are currently trading up 13% on its start price, at a little over $18.
DaltonTx gets grant for AI-enabled TB drug hunt
London, UK start-up DaltonTx has been awarded a grant by the Gates Foundation to advance tuberculosis (TB) drug discovery programmes using its AI-enabled platform, Dalton.
The award – the value of which is undisclosed – will support large-scale computational screening of TB pathogen Mycobacterium tuberculosis to find new chemical starting points for treatments. Meanwhile, in collaboration with the non-profit organisation Ersilia, the project plans to make its models, workflows, and datasets open-access, to help lower-resource labs "across the Global South," said the company in a statement.
Dalton is designed to handle the full drug discovery process, from raw data and model training to molecular design, synthesis, and decision-making, creating a "continuous learning engine" for both small-molecule and biologic medicines, according to DaltonTx.
Danaher, NVIDIA join forces on autonomous AI-powered labs
Lab product specialist Danaher has called on tech giant NVIDIA to help it develop AI-enabled, autonomous laboratory systems that can accelerate scientific research.
The companies will work to combine Danaher's scientific instrumentation, automation technologies, laboratory workflow software, and domain expertise with NVIDIA accelerated computing and AI technologies, to help researchers "move faster from prediction to experimental evidence."
Earlier this month, Danaher said it is working on its first autonomous AI lab, scheduled to operate at scale in early 2027 and deliver improvements such as faster discovery of affinity reagents and increased annual reagent generation. The goal is to help researchers move faster from prediction to experimental evidence, creating a continuous learning cycle where experiments inform models and models help design better experiments.
GSK signs up with Chai Discovery after tech evaluation
San Francisco-based Chai Discovery's work with GSK has been upgraded from a technology evaluation to a full-blown partnership, giving the UK big pharma access to Chai's platform, including its protein folding and design models, for discovery efforts across its pipeline.
In the evaluation, Chai's models generated designs to GSK targets in "zero-shot" fashion, i.e., without target-specific training. GSK conducted internal wet-lab testing of the designs, finding binders to all tested targets.
The new alliance with GSK comes in a transformational year for Chai, which has signed a string of other partnerships with Bristol Myers Squibb, Eli Lilly, Novartis, and Pfizer, and raised an impressive $400 million in third-round financing.
"We evaluated their models across a panel of diverse targets and saw designs with strong binding affinities," said Christopher Austin, head of R&D technologies at GSK. "Their technology complements our own internal models that we continuously retrain against our own wet-lab data, all helping to enable us to accelerate the discovery of potential new medicines."
Image by Gerd Altmann from Pixabay
